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Národní úložiště šedé literatury Nalezeno 4 záznamů.  Hledání trvalo 0.00 vteřin. 
Urban Element Detection Using Satellite Imagery
 Oravec, Dávid ; Herout, Adam (oponent) ; Zlámal, Adam (vedoucí práce)
This thesis focuses on the right detection of objects in satellite imagery using convolutional neural networks. The goal of the thesis is to detect swimming pools and tennis courts in satellite imagery from different cities using the trained model. The model works with data from 10 different cities. The RetinaNet neural network model and Detectron2 library were used for development. The final trained model can detect objects with the average precision (AP50) at the level of 63.402 %. The thesis can be useful in the field of automating the acquisition of land surface statistics.
Úplný záznam
Detection, Extraction and Measurement of the Contour and Circumference of the Metacarpal Bones in X-Rays of the Human Hand
 Otčenáš, Matej ; Dvořák, Michal (oponent) ; Drahanský, Martin (vedoucí práce)
This thesis aims to detect and subsequently extract the contour of the third metacarpal bone of the human hand from X-ray images and measure the circumference. The thesis describes segmentation of image using various methods for object detection which will be used for eventual measurements.
Úplný záznam
Detection, Extraction and Measurement of the Contour and Circumference of the Metacarpal Bones in X-Rays of the Human Hand
 Otčenáš, Matej ; Dvořák, Michal (oponent) ; Drahanský, Martin (vedoucí práce)
This thesis aims to detect and subsequently extract the contour of the third metacarpal bone of the human hand from X-ray images and measure the circumference. The thesis describes segmentation of image using various methods for object detection which will be used for eventual measurements.
Úplný záznam
Urban Element Detection Using Satellite Imagery
 Oravec, Dávid ; Herout, Adam (oponent) ; Zlámal, Adam (vedoucí práce)
This thesis focuses on the right detection of objects in satellite imagery using convolutional neural networks. The goal of the thesis is to detect swimming pools and tennis courts in satellite imagery from different cities using the trained model. The model works with data from 10 different cities. The RetinaNet neural network model and Detectron2 library were used for development. The final trained model can detect objects with the average precision (AP50) at the level of 63.402 %. The thesis can be useful in the field of automating the acquisition of land surface statistics.
Úplný záznam

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